Long Term Evolution (LTE) is a Universal Mobile Telecommunications System (UMTS) technical standard formulated by The 3rd Generation Partnership Project (3GPP) organization. An LTE access network load is defined as an occupancy rate of Physical Resource Block (PRB); a higher occupancy rate indicates a higher air interface load. When an air interface is overloaded, a s Self-Organized Network (SON)/Radio Resource Management (RRM) entity of a base station needs to apply a given policy to perform network optimization, so as to meet service requirements of users.
In the prior art, when a base station detects an excessively high air interface load, a SON entity proactively triggers a load balancing operation, and hands over cell edge users to a neighboring cell with a lower load, thereby reducing a cell load and improving cell performance. However, in this solution, a cause for overload cannot be distinguished when a cell is overloaded. There may be many causes for cell overload. For example: (1) When a cell has an excessively high service requirement, a PRB quantity in the service requirement exceeds a quantity of resources of a base station, resulting in system overload; (2) When a Signal to Noise Ratio (SNR) of a received signal is quite low for a large quantity of users in a cell, even if a service requirement is not high, system overload may be caused by the fact that due to poor channel quality, more resources than available PRB resources of a base station are needed to meet the service requirement; (3) When a Signal to Interference Ratio (SIR) is very low because a large quantity of users in a cell are interfered, even if a service requirement is not high, system overload may be caused by the fact that due to poor channel quality, more resources than available PRB resources of a base station are needed to meet the service requirement; and (4) It should also be considered that because resource usage features for a Guaranteed Bit Rate (GBR) service and a None Guaranteed Bit Rate (NGBR) service are different, different service types have different effects on a cell load. As a result, simply performing a load balancing optimization operation cannot effectively improve a load status of an overloaded cell in many scenarios. For example, for cell overload caused by interference from a neighboring cell, if some users are handed over to the neighboring cell, the other users in the cell are interfered with by the neighboring cell more seriously. For another example, when there are many cell center users and few cell edge users, cell overload is mainly caused by a large quantity of service requirements of the cell center users; therefore, if the cell edge users are handed over to a neighboring cell only by means of load balancing, a load status of the cell cannot be effectively improved either.